Hexanucleotide expansion in has been related to several phenotypes to date, complicating the clinical recognition of these neurodegenerative disorders. An early diagnosis can improve the management of patients, promoting early administration of therapeutic supportive strategies. Here, we report known clinical presentations of -related neurodegenerative disorders, pointing out suggestive phenotypes that can benefit the genetic characterization of patients. Considering the high variability of -related disorder, frequent and rare manifestations are described, with detailed clinical, instrumental evaluation, and supportive therapeutical approaches. Furthermore, to improve the understanding of molecular pathways of the disease and potential therapeutical targets, a detailed description of the cellular mechanisms related to the pathological effect of is reported. New promising therapeutical strategies and ongoing studies are reported highlighting their molecular role in cellular pathological pathways of . These therapeutic approaches are particularly promising because they seem to stop the disease before neuronal damage. The knowledge of clinical and molecular features of -related neurodegenerative disorders improves the therapeutical application of known strategies and will lay the basis for the development of new potential therapies.
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http://dx.doi.org/10.3389/fnagi.2022.907122 | DOI Listing |
Alzheimers Res Ther
January 2025
Department of Neurology, University Medical Center Rostock, 18147, Rostock, Germany.
Background: Degeneration of the basal forebrain cholinergic system is a hallmark feature shared by Alzheimer's disease (AD) and Lewy body disease (LBD) whereas hippocampus atrophy is more specifically related to AD. We aimed to investigate the relationship between basal forebrain and hippocampus atrophy, cognitive decline, and neuropathology in a large autopsy sample.
Methods: Data were obtained from the National Alzheimer's Coordinating Center (NACC).
Alzheimers Res Ther
January 2025
Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Sankt Augustin, Germany.
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting millions worldwide, leading to cognitive and functional decline. Early detection and intervention are crucial for enhancing the quality of life of patients and their families. Remote Monitoring Technologies (RMTs) offer a promising solution for early detection by tracking changes in behavioral and cognitive functions, such as memory, language, and problem-solving skills.
View Article and Find Full Text PDFTransl Neurodegener
January 2025
Department of Biochemistry, College of Medicine, Konyang University, 158, Gwanjeodong-Ro Seo-Gu, Daejeon, 35365, Republic of Korea.
Alzheimer's disease (AD) is the most common type of dementia. Monoclonal antibodies (MABs) serve as a promising therapeutic approach for AD by selectively targeting key pathogenic factors, such as amyloid-β (Aβ) peptide, tau protein, and neuroinflammation. Specifically, based on their efficacy in removing Aβ plaques from the brains of patients with AD, the U.
View Article and Find Full Text PDFMol Psychiatry
January 2025
Telethon Institute of Genetics and Medicine, Via Campi Flegrei 34, Pozzuoli, 80078, Naples, Italy.
Lysosomal storage disorders characterized by defective heparan sulfate (HS) degradation, such as Mucopolysaccharidosis type IIIA-D (MPS-IIIA-D), result in neurodegeneration and dementia in children. However, dementia is preceded by severe autistic-like behaviours (ALBs), presenting as hyperactivity, stereotypies, social interaction deficits, and sleep disturbances. The absence of experimental studies on ALBs' mechanisms in MPS-III has led clinicians to adopt symptomatic treatments, such as antipsychotics, which are used for non-genetic neuropsychiatric disorders.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
An essential task in spatial transcriptomics is identifying spatially variable genes (SVGs). Here, we present Celina, a statistical method for systematically detecting cell type-specific SVGs (ct-SVGs)-a subset of SVGs exhibiting distinct spatial expression patterns within specific cell types. Celina utilizes a spatially varying coefficient model to accurately capture each gene's spatial expression pattern in relation to the distribution of cell types across tissue locations, ensuring effective type I error control and high power.
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